Subcarrier and Power Allocation in WiMAX

Worldwide Interoperability for Microwave Access (WiMAX) is one of the latest technologies for providing Broadband Wireless Access (BWA) in a metropolitan area. The use of orthogonal frequency division multiplexing (OFDM) transmissions has been proposed in WiMAX to mitigate the complications which are associated with frequency selective channels. In addition, the multiple access is achieved by using orthogonal frequency division multiple access (OFDMA) scheme which has several advantages such as flexible resource allocation, relatively simple transceivers, and high spectrum efficient. In OFDMA the controllable resources are the subcarriers and the allocated power per subband. Moreover, adaptive subcarrier and power allocation techniques have been selected to exploit the natural multiuser diversity. This leads to an improvement of the performance by assigning the proper subcarriers to the user according to their channel quality and the power is allocated based on water-filling algorithm. One simple method is to allocate subcarriers and powers equally likely between all users. It is well known that this method reduces the spectral efficiency of the system, hence, it is not preferred unless in some applications. In order to handle the spectral efficiency problem, in this thesis we discuss three novel resources allocation algorithms for the downlink of a multiuser OFDM system and analyze the algorithm performances based on capacity and fairness measurement. Our intensive simulations validate the algorithm performances.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

The Capital Improvement Plan Environmental Assessment Process

This report contains one explicit mention of Waller Creek and how a Convention Center 66" Water Transmission Line Relocation resulted in a recommendation for the restoration of Waller Creek banks.This report outlines the current requirements for Environmental Assessments (EAs) performed for compliance with the City of Austin Land Development Code (LDC) as they are applied in City Capital Improvement Plan (CIP) projects. Much of this information is not currently documented in either the Environmental Criteria Manual (ECM) or other material readily available to Public Works Project Managers. An overview of the Environmental Assessment process is provided along with the goals for CIP assessments, methods for review and completion of assessments, and recommendations for improving the City processes. Attachments to this report include pertinent LDC citations, the form in use for project identification, a suggested process for conducting and reviewing assessments a scope of work for staff or consultants performing assessments, and photographic summaries of critical environmental features to be protected in accordance with the LDC in City as well as private projects. Also, a flowchart of the EA review process and a brief summary of assessments of past projects are included in the attachments. The information is provided as a precursor to the expansion of the current ECM section on Environmental Assessments in Section 1.3.0 and for consideration by the Public Works Department and other Project Managers for early review of environmental impacts, leading to better CIP projects..Waller Creek Working Grou

A Multi-Service Oriented Multiple-Access Scheme for Next-Generation Mobile Networks

One of the key requirements for fifth-generation (5G) cellular networks is their ability to handle densely connected devices with different quality of service (QoS) requirements. In this article, we present multi-service oriented multiple access (MOMA), an integrated access scheme for massive connections with diverse QoS profiles and/or traffic patterns originating from both handheld devices and machine-to-machine (M2M) transmissions. MOMA is based on a) stablishing separate classes of users based on relevant criteria that go beyond the simple handheld/M2M split, b) class dependent hierarchical spreading of the data signal and c) a mix of multiuser and single-user detection schemes at the receiver. Practical implementations of the MOMA principle are provided for base stations (BSs) that are equipped with a large number of antenna elements. Finally, it is shown that such a massive-multiple-input-multiple-output (MIMO) scenario enables the achievement of all the benefits of MOMA even with a simple receiver structure that allows to concentrate the receiver complexity where effectively needed.Comment: 6 pages, 3 figures, accepted to the European Conference on Networks and Communications (EuCNC 2016

Data Provenance and Management in Radio Astronomy: A Stream Computing Approach

New approaches for data provenance and data management (DPDM) are required for mega science projects like the Square Kilometer Array, characterized by extremely large data volume and intense data rates, therefore demanding innovative and highly efficient computational paradigms. In this context, we explore a stream-computing approach with the emphasis on the use of accelerators. In particular, we make use of a new generation of high performance stream-based parallelization middleware known as InfoSphere Streams. Its viability for managing and ensuring interoperability and integrity of signal processing data pipelines is demonstrated in radio astronomy. IBM InfoSphere Streams embraces the stream-computing paradigm. It is a shift from conventional data mining techniques (involving analysis of existing data from databases) towards real-time analytic processing. We discuss using InfoSphere Streams for effective DPDM in radio astronomy and propose a way in which InfoSphere Streams can be utilized for large antennae arrays. We present a case-study: the InfoSphere Streams implementation of an autocorrelating spectrometer, and using this example we discuss the advantages of the stream-computing approach and the utilization of hardware accelerators

Bandwidth allocation for wireless multimedia systems.

Chen Chung-Shue.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 100-102).Abstracts in English and Chinese.Chapter 1. --- Introduction --- p.1Chapter 1.1 --- Evolution to 3G Mobile --- p.2Chapter 1.1.1 --- First Generation --- p.2Chapter 1.1.2 --- Second Generation --- p.3Chapter 1.1.3 --- Third Generation --- p.3Chapter 1.2 --- UTRA Framework --- p.5Chapter 1.2.1 --- FDD and TDD --- p.6Chapter 1.2.2 --- Channel Spreading --- p.6Chapter 1.2.3 --- OVSF Code Tree --- p.8Chapter 1.3 --- Cellular Concepts --- p.10Chapter 1.3.1 --- System Capacity --- p.10Chapter 1.3.2 --- Multiple Access --- p.11Chapter 1.3.3 --- Resource Management --- p.15Chapter 1.4 --- Organization of the Thesis --- p.16Chapter 2. --- Analysis on Multi-rate Operations --- p.18Chapter 2.1 --- Related Works in Multi-rate Operations --- p.18Chapter 2.1.1 --- Variable Spreading Factor --- p.19Chapter 2.1.2 --- Data Time-multiplexing --- p.20Chapter 2.1.3 --- Multi-carrier Transmission --- p.21Chapter 2.1.4 --- Hybrid TDMA/CDMA --- p.23Chapter 2.2 --- Problems in Multi-rate Operations --- p.24Chapter 2.2.1 --- Conventional CDMA --- p.24Chapter 2.2.2 --- Data Time-multiplexing --- p.25Chapter 2.2.3 --- MC-CDMA --- p.25Chapter 2.2.4 --- TD-CDMA --- p.27Chapter 2.3 --- Multi-user multi-rate Operations --- p.28Chapter 3. --- Bandwidth Allocation --- p.29Chapter 3.1 --- Most Regular Binary Sequence --- p.30Chapter 3.1.1 --- Properties of MRBS --- p.31Chapter 3.1.2 --- Construction of MRCS --- p.32Chapter 3.1.3 --- Zero-one Sequence under MRBS --- p.33Chapter 3.2 --- MRBS in TD-CDMA --- p.35Chapter 3.2.1 --- Time Slot Optimization --- p.36Chapter 3.2.2 --- Sequence Generator --- p.37Chapter 3.3 --- Most Regular Code Sequence --- p.38Chapter 3.3.1 --- Properties of MRCS --- p.38Chapter 3.2.2 --- Construction of MRCS --- p.41Chapter 3.3.3 --- Fraction-valued Sequence under MRCS --- p.42Chapter 3.3.4 --- LCC and UCC --- p.45Chapter 3.4 --- MRCS in WCDMA --- p.46Chapter 3.4.1 --- Spreading Factor Optimization --- p.46Chapter 3.4.2 --- Code Generator --- p.48Chapter 3.4.3 --- Uplink and Downlink --- p.50Chapter 4. --- Multi-access Control --- p.52Chapter 4.1 --- Conflict and Resolution --- p.53Chapter 4.1.1 --- Conflicts in MRBS and MRCS --- p.53Chapter 4.1.2 --- Resolution with Buffering --- p.55Chapter 4.2 --- MRBS Transmission Scheduling --- p.56Chapter 4.2.1 --- Slot Scheduling on MRBS --- p.56Chapter 4.2.2 --- Properties of Scheduling Algorithm --- p.59Chapter 4.2.3 --- Scheduled MRBS --- p.71Chapter 4.3 --- MRCS Transmission Scheduling --- p.73Chapter 4.3.1 --- Slot Scheduling on MRCS --- p.73Chapter 4.3.2 --- Properties of Scheduling Algorithm --- p.75Chapter 4.3.3 --- Scheduled MRBS --- p.76Chapter 4.4 --- Performance Evaluation --- p.78Chapter 4.4.1 --- Simulation on Algorithm --- p.78Chapter 4.4.2 --- Resource Utilization and Delay Bound --- p.79Chapter 4.4.3 --- Blocking Model and System Capacity --- p.80Chapter 4.4.4 --- Numerical Analysis --- p.86Chapter 5. --- Conclusions and Future works --- p.92Appendix A --- p.94Appendix B --- p.98Bibliography --- p.10

Medium access control in wireless network-on-chip: a context analysis

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Wireless on-chip communication is a promising candidate to address the performance and efficiency issues that arise when scaling current NoC techniques to manycore processors. A WNoC can serve global and broadcast traffic with ultra-low latency even in thousand-core chips, thus acting as a natural complement to conventional and throughput-oriented wireline NoCs. However, the development of MAC strategies needed to efficiently share the wireless medium among the increasing number of cores remains a considerable challenge given the singularities of the environment and the novelty of the research area. In this position article, we present a context analysis describing the physical constraints, performance objectives, and traffic characteristics of the on-chip communication paradigm. We summarize the main differences with respect to traditional wireless scenarios, and then discuss their implications on the design of MAC protocols for manycore WNoC, with the ultimate goal of kickstarting this arguably unexplored research area.Peer ReviewedPostprint (author's final draft

IEEE 802.11 기반 Enterprise 무선 LAN을 위한 자원 관리 기법

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 전기·컴퓨터공학부, 2019. 2. 전화숙.IEEE 802.11이 무선 LAN (wireless local area network, WLAN)의 실질적인 표준이 됨에 따라 수 많은 엑세스 포인트(access points, APs)가 배치되었고, 그 결과 WLAN 밀집 환경이 조성되었다. 이러한 환경에서는, 이웃한 AP들에 동일한 채널을 할당하는 문제를 피할 수 없으며, 이는 해당 AP들이 같은 채널을 공유하게 하고 그로 인한 간섭을 야기한다. 간섭으로 인한 성능 저하를 줄이기 위해 채널 할당(channelization) 기법이 중요하다. 또한, 한 조직이 특정 지역에 밀집 배치된 AP들을 관리한다면 특정 사용자를 서비스할 수 있는 AP가 여럿일 수 있다. 이 경우, 사용자 접속(user association, UA) 기법이 준정적(quasi-static) 환경과 차량 환경 모두에서 네트워크 성능에 큰 영향을 미친다. 본 논문에서는 밀집 배치된 WLAN 환경에서 와이파이(WiFi) 성능 향상을 위해 채널 할당 기법을 제안한다. 먼저, 제안한 기법에서는 각각의 AP에 채널을 할당하기 위해 간섭 그래프(interference graph)를 이용하며 채널 결합(channel bonding)을 고려한다. 다음으로, 주어진 채널 결합 결과를 기반으로 해당 AP가 동적 채널 결합을 지원하는지 여부에 따라 주 채널(primary channel)을 결정한다. 한편, 준정적 환경과 차량 환경에서의 UA 문제는 다소 차이가 있다. 따라서 본 논문에서는 각각의 환경에 따라 서로 다른 UA 기법을 설계하였다. 준정적 환경에서의 UA 기법은 멀티캐스트 전송, 다중 사용자 MIMO (multi-user multiple input multiple output), 그리고 AP 수면과 같은 다양한 기술과 함께 AP간의 부하 분산(load balancing)과 에너지 절약을 고려한다. 제안하는 기법에서 UA 문제는 다목적함수 최적화 문제로 정식화하였고 그 해를 구하였다. 차량 환경에서의 UA 기법은 핸드오버(handover, HO) 스케줄 문제로 귀결된다. 본 논문에서는 도로의 지형을 고려하여 사용자가 접속할 AP를 결정하는 HO 스케줄 기법을 제안한다. 사용자는 단지 다음 AP로 연결을 맺을 시기만 결정하면 되기 때문에, 차량 환경에서의 매우 빠르고 효율적인 HO 기법을 구현할 수 있다. 이를 위해, 그래프 모델링 기법(graph modeling technique)을 활용하여 도로를 따라 배치된 AP사이의 관계를 표현한다. 현실적인 시나리오를 위해 직선 구간, 우회 구간, 교차로, 그리고 유턴 구간 등을 포함하는 복잡한 도로 구조를 고려한다. 도로 구조를 고려하여 각 사용자의 이동 경로를 예측하고, 그에 기반하여 각 사용자 별 HO의 목적 AP 집합을 선택한다. 제안하는 HO 스케줄 기법의 설계 목적은 HO 지연 시간의 합을 최소화하고 각 AP에서 해당 채널을 사용하려는 사용자 수를 줄이면서 WiFi 연결 시간을 최대화하는 것이다. 마지막으로, 본 논문에서는 준정적 환경에서 제안한 채널 할당 기법과 UA 기법의 현실성을 증명하기 위한 시험대(testbed)를 구성하였다. 또한, 광범위한 시뮬레이션을 통해 준정적 환경과 차량 환경에서 제안한 기법들과 기존의 기법들의 성능을 비교하였다.As the IEEE 802.11 (WiFi) becomes the defacto global standard for wireless local area network (WLAN), a huge number of WiFi access points (APs) are deployed. This condition leads to a densely deployed WLANs. In such environment, the conflicting channel allocation between the neighboring access points (APs) is unavoidable, which causes the channel sharing and interference between APs. Thus, the channel allocation (channelization) scheme has a critical role to tackle this issue. In addition, when densely-deployed APs covering a certain area are managed by a single organization, there can exist multiple candidate APs for serving a user. In this case, the user association (UA), i.e., the selection of serving AP, holds a key role in the network performance both in quasi-static and vehicular environments. To improve the performance of WiFi in a densely deployed WLANs environment, we propose a channelization scheme. The proposed channelization scheme utilizes the interference graph to assign the channel for each AP and considers channel bonding. Then, given the channel bonding assignment, the primary channel location for each AP is determined by observing whether the AP supports the static or dynamic channel bonding. Meanwhile, the UA problem in the quasi-static and vehicular environments are slightly different. Thus, we devise UA schemes both for quasi-static and vehicular environments. The UA schemes for quasi-static environment takes account the load balancing among APs and energy saving, considering various techniques for performance improvement, such as multicast transmission, multi-user MIMO, and AP sleeping, together. Then, we formulate the problem into a multi-objective optimization and get the solution as the UA scheme. On the other hand, the UA scheme in the vehicular environment is realized through handover (HO) scheduling mechanism. Specifically, we propose a HO scheduling scheme running on a server, which determines the AP to which a user will be handed over, considering the road topology. Since a user only needs to decide when to initiate the connection to the next AP, a very fast and efficient HO in the vehicular environment can be realized. For this purpose, we utilize the graph modeling technique to map the relation between APs within the road. We consider a practical scenario where the structure of the road is complex, which includes straight, curve, intersection, and u-turn area. Then, the set of target APs for HO are selected for each user moving on a particular road based-on its moving path which is predicted considering the road topology. The design objective of the proposed HO scheduling is to maximize the connection time on WiFi while minimizing the total HO latency and reducing the number of users which contend for the channel within an AP. Finally, we develop a WLAN testbed to demonstrate the practicality and feasibility of the proposed channelization and UA scheme in a quasi-static environment. Furthermore, through extensive simulations, we compare the performance of the proposed schemes with the existing schemes both in quasi-static and vehicular environments.1 Introduction 1.1 Background and Motivation 1.2 Related Works 1.3 Research Scope and Proposed Schemes 1.3.1 Centralized Channelization Scheme for Wireless LANs Exploiting Channel Bonding 1.3.2 User Association for Load Balancing and Energy Saving in Enterprise WLAN 1.3.3 A Graph-Based Handover Scheduling for Heterogenous Vehicular Networks 1.4 Organization 2 Centralized Channelization Scheme for Wireless LANs Exploiting Channel Bonding 2.1 System Model 2.2 Channel Sharing and Bonding 2.2.1 Interference between APs 2.2.2 Channel Sharing 2.2.3 Channel Bonding 2.3 Channelization Scheme 2.3.1 Building Interference Graph 2.3.2 Channel Allocation 2.3.3 Primary Channel Selection 2.4 Implementation 3 User Association for Load Balancing and Energy Saving in Enterprise Wireless LANs 3.1 System Model 3.1.1 IEEE 802.11 ESS-based Enterprise WLAN 3.1.2 Downlink Achievable Rate for MU-MIMO Groups 3.1.3 Candidate MU-MIMO Groups 3.2 User Association Problem 3.2.1 Factors of UA Objective 3.2.2 Problem Formulation 3.3 User Association Scheme 3.3.1 Equivalent Linear Problem 3.3.2 Solution Algorithm 3.3.3 Computational Complexity (Execution Time) 3.4 Implementation 4 A Graph-Based Handover Scheduling for Heterogenous Vehicular Networks 4.1 System Model 4.2 Graph-Based Modeling 4.2.1 Division of Road Portion into Road Segments 4.2.2 Relation between PoAs on a Road Segment 4.2.3 Directed Graph Representation 4.3 Handover Scheduling Problem 4.3.1 Problem Formulation 4.3.2 Weight of Edge 4.3.3 HO Scheduling Algorithm 4.4 Handover Scheduling Operation 4.4.1 HO Schedule Delivery 4.4.2 HO Triggering and Execution 4.4.3 Communication Overhead 5 Performance Evaluation 5.1 CentralizedChannelizationSchemeforWirelessLANsExploitingChannel Bonding 5.1.1 Experiment Settings 5.1.2 Comparison Schemes 5.1.3 Preliminary Experiment for Building Interference Graph 5.1.4 Experiment Results 5.2 User Association for Load Balancing and Energy Saving in Enterprise Wireless LANs 5.2.1 Performance Metrics 5.2.2 Experiment Settings 5.2.3 Experiment Results 5.2.4 Simulation Settings 5.2.5 Comparison Schemes 5.2.6 Simulation Results 5.2.7 Simulation for MU-MIMO System 5.3 A Graph-BasedHandover Scheduling for Heterogenous Vehicular Networks 5.3.1 Performance Metrics 5.3.2 Simulation Settings 5.3.3 Simulation Results 6 Conculsion Bibliography AcknowledgementsDocto